Scientific Program
Session Summary:
Artificial intelligence (AI) is rapidly transforming diagnostic medicine, yet its true value in transplant pathology remains a subject of active debate. This webinar will bring together experts in thoracic transplantation, pathology, and imaging to examine the current and future role of AI in the assessment of heart and lung allografts.
The session will explore how machine learning and computational pathology are being applied to improve the detection, characterization, and prognostication of transplant-related injury and rejection. Through three complementary presentations, participants will gain insight into AI-driven tools for cardiac allograft rejection assessment, lung allograft injury and rejection, and the integration of imaging biomarkers with AI for transplant monitoring.
Speakers will discuss the potential of AI to enhance diagnostic accuracy, reduce interobserver variability, and support precision medicine, while also addressing current limitations, validation challenges, and barriers to clinical implementation.
Designed for pathologists, transplant physicians, radiologists, researchers, and trainees, this webinar will provide a balanced perspective on whether AI is ready to become a practical tool in thoracic transplantation.
Format: 60-minute Webinar, Panel Discussion and Q&A at end of session
Moderators:
Vanathi Sivasubramaniam, St Vincent's Hospital Sydney, Sidney, Australia.
Fiorella Calabrese, University of Padova, Padova, Italy.
Presentation 1: Decoding Cardiac Allograft Rejection: Can AI See What We Miss?
Speaker: Eliot G. Peyster, University of Pennsylvania, Philadelphia, PA, USA
Presentation 2: Beyond Patterns: AI-Guided Insights in Lung Allograft Injury and Rejection
Speaker: Jan von der Thüsen, Erasmus MC, Rotterdam, The Netherlands.
Presentation 3: From Pixels to Prognosis: Imaging Biomarkers and AI in Thoracic Transplant Monitoring
Speaker: Chandra Bortolotto, University of Pavia, Pavia, Italy
Q&A (15 minutes)